{
 "metadata": {
  "name": "WAFO Chapter 2"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "CHAPTER2 Modelling random loads and stochastic waves\n",
      "====================================================\n",
      "\n",
      "Chapter2 contains the commands used in Chapter 2 of the tutorial and present some tools for analysis of random functions with respect to their correlation, spectral and distributional properties. The presentation is divided into three examples: \n",
      "\n",
      "Example1 is devoted to estimation of different parameters in the model.\n",
      "Example2 deals with spectral densities and\n",
      "Example3 presents the use of WAFO to simulate samples of a Gaussian process.\n",
      "\n",
      "Some of the commands are edited for fast computation. \n",
      "\n",
      "Section 2.1 Introduction and preliminary analysis\n",
      "=================================================\n",
      "\n",
      "Example 1: Sea data\n",
      "-------------------\n",
      "Observed crossings compared to the expected for Gaussian signals\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import wafo\n",
      "import wafo.objects as wo\n",
      "xx = wafo.data.sea()\n",
      "me = xx[:, 1].mean()\n",
      "sa = xx[:, 1].std()\n",
      "xx[:, 1] -= me\n",
      "ts = wo.mat2timeseries(xx)\n",
      "tp = ts.turning_points()\n",
      "\n",
      "cc = tp.cycle_pairs()\n",
      "lc = cc.level_crossings()\n",
      "lc.plot()\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEVCAYAAAD+TqKGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n"
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Average number of upcrossings per time unit\n",
      "----------------------------------------------\n",
      "Next we compute the mean frequency as the average number of upcrossings per time unit of the mean level (= 0); this may require interpolation in the crossing intensity curve, as follows.  \n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "T = xx[:, 0].max() - xx[:, 0].min()\n",
      "f0 = np.interp(0, lc.args, lc.data, 0) / T  #! zero up-crossing frequency \n",
      "print('f0 = %g' % f0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "f0 = 0.224071\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Turningpoints and irregularity factor\n",
      "----------------------------------------"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fm = len(tp.data) / (2 * T)   # frequency of maxima\n",
      "alfa = f0 / fm                # approx Tm24/Tm02\n",
      "\n",
      "print('fm = %g, alpha = %g, ' % (fm, alfa))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "fm = 0.456159, alpha = 0.491212, \n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Visually examine data\n",
      "------------------------\n",
      "We finish this section with some remarks about the quality of the measured data. Especially sea surface measurements can be of poor quality. We shall now check the  quality of the dataset {\\tt xx}. It is always good practice to visually examine the data before the analysis to get an impression of the quality, \n",
      "non-linearities and narrow-bandedness of the data.First we shall plot the data and zoom in on a specific region. A part of sea data is visualized with the following commands"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "ts.plot_wave('k-', tp, '*', nfig=1, nsub=1)\n",
      "\n",
      "axis([0, 2, -2, 2])\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEXCAYAAACqIS9uAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n"
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finding possible spurious points\n",
      "------------------------------------\n",
      "However, if the amount of data is too large for visual examinations one could use the following criteria to find possible spurious points. One must be careful using the criteria for extremevalue analysis, because\n",
      "it might remove extreme waves that are OK and not spurious."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import wafo.misc as wm\n",
      "dt = ts.sampling_period()\n",
      "# dt = np.diff(xx[:2,0])\n",
      "dcrit = 5 * dt\n",
      "ddcrit = 9.81 / 2 * dt * dt\n",
      "zcrit = 0\n",
      "inds, indg = wm.findoutliers(ts.data, zcrit, dcrit, ddcrit, verbose=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Found 0 spurious positive jumps of Dx\n",
        "Found 0 spurious negative jumps of Dx\n",
        "Found 37 spurious positive jumps of D^2x\n",
        "Found 200 spurious negative jumps of D^2x\n",
        "Found 244 consecutive equal values\n",
        "Found the total of 1152 spurious points\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Section 2.2 Frequency Modeling of Load Histories\n",
      "---------------------------------------------------\n",
      "Periodogram: Raw spectrum"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "Lmax = 9500\n",
      "S = ts.tospecdata(L=Lmax)\n",
      "S.plot()\n",
      "axis([0, 5, 0, 0.7])\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEXCAYAAAC3c9OwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztnXl8TOf+xz+TpUiIWCsSBNGIPSRiCWKNKKEoSouWNu0P\nt67qbV1d6HJbpdqqezVtkWspaVVxLWmqpFVKLClto8QSRohIrZF98vz+OD0z58ycmTlnlpyZyff9\neuU1Z3nO83zPmcn3c77PqmGMMRAEQRCEEV5qG0AQBEG4JiQQBEEQhCQkEARBEIQkJBAEQRCEJCQQ\nBEEQhCQkEARBEIQkJBAE4QSmT5+OV199VVba3NxceHl5oaqqymn2bNy4EfHx8U7Ln/BMSCAIl+an\nn35Cnz59EBgYiEaNGiE2NhbHjh1zapmhoaHYt2+fXXloNBpoNBoHWWQ/U6ZMwbfffqvf9/LywoUL\nF1S0iHAHfNQ2gCDMcffuXYwcORLJycmYMGECysrKcODAAdSqVcup5Wo0GlgaP1pZWQkfH+v/Oq4+\nBtXV7SPUhyIIwmU5e/YsNBoNJk6cCI1Gg9q1a2Po0KHo3LkzACAlJQV9+/bFnDlzEBgYiIiICNGb\n/507dzBjxgw0b94cISEhePXVV0XVOJ999hk6dOiAgIAAdOzYEVlZWXjiiSdw+fJljBo1CvXq1cOy\nZcv0VUBr1qxBq1atMGTIEADAo48+iqCgIAQGBmLAgAHIzs6WdV9VVVWYP38+mjRpgrZt22LXrl2i\n85bsTklJQWxsLF588UU0bNgQbdq0QVpamv7alJQUtG3bFgEBAWjTpg2++OIL/fF+/foBAPr37w8A\n6Nq1KwICAvDll1+ic+fO2Llzpz6fiooKNG7cGCdPnpT3ZRGeCSMIF+Xu3busUaNGbNq0aWzPnj3s\n5s2bovNr165lPj4+7MMPP2SVlZUsNTWV1a9fn926dYsxxtiYMWPYs88+y4qLi1lBQQHr2bMnS05O\nZowx9uWXX7Lg4GB27Ngxxhhj586dY5cuXWKMMRYaGsq+//57fTkXL15kGo2GTZs2jRUXF7PS0lJ9\n+UVFRay8vJzNnTuXdevWTX/N9OnT2SuvvCJ5X6tWrWLt27dnV65cYTdv3mRxcXHMy8uL6XQ6q3av\nXbuW+fr6ss8//5xVVVWxVatWsebNmzPGGCsqKmIBAQHs7NmzjDHG8vPz2e+//66/LjY2Vm+DRqNh\n58+f1++/9957bOLEifr9bdu2sS5dusj4lghPhgSCcGlOnz7Npk+fzkJCQpiPjw9LTExk169fZ4xx\nTo93jjw9e/Zk69evZ/n5+axWrVqspKREf+6LL75gAwcOZIwxNmzYMLZixQrJMs0JxMWLF83aeevW\nLabRaNjdu3cZY5YFYuDAgXqHzxhj6enpTKPRMJ1OZ9XutWvXsrCwMP25+/fvM41Gw65fv86KiopY\nYGAg+/rrr1lxcbGoTGsCkZeXx+rWrcvu3bvHGGNs3LhxbOnSpWbvl6gZUBUT4dK0b98ea9euhVar\nxW+//YarV69i7ty5+vPBwcGi9K1atcLVq1dx+fJlVFRUICgoCA0aNECDBg3w7LPP4saNGwCAK1eu\noG3btopsadGihX67qqoKL7/8MsLCwlC/fn20bt0aAFBYWGg1n2vXronyatmypX770qVLFu0GgGbN\nmum3/fz8AABFRUXw9/dHamoqPvnkEzRv3hwjR47EmTNnZN1b8+bN0bdvX2zZsgW3b99GWloapkyZ\nIutawnOhRmrCbQgPD8e0adPw6aef6o/l5eWJ0ly6dAmjR49GixYtUKtWLfz555/w8jJ9D2rRogXO\nnTsnWY653kfC4xs3bsSOHTvw/fffo1WrVrh9+zYaNmwoq+E3KCgIly9f1u8Lt63ZbY1hw4Zh2LBh\nKCsrw8KFC/H000/jxx9/lHXttGnTsHr1alRUVKBPnz4ICgpSXD7hWVAEQbgsZ86cwfLly/UioNVq\nsWnTJvTu3VufpqCgACtWrEBFRQW++uor/PHHHxgxYgSaNWuGYcOGYd68ebh37x6qqqpw/vx5vbOc\nOXMmli1bhhMnToAxhnPnzukd9YMPPojz589btK2oqAi1atVCw4YNcf/+ffzzn/8UnbckFBMmTMCK\nFSuQl5eHW7du4d1339WfCwoKsmi3JQoKCrB9+3bcv38fvr6+8Pf3h7e3t2RaqXt85JFHcOLECaxY\nsQJTp061Wh7h+ZBAEC5LvXr1cOTIEcTExKBu3bro3bs3unTpgvfff1+fJiYmBjk5OWjSpAleffVV\nfP3112jQoAEAYN26dSgvL0eHDh3QsGFDPProo8jPzwcAjB8/HgsXLsTkyZMREBCAsWPH4tatWwCA\nBQsW4K233kKDBg2wfPlyAKZRxdSpU9GqVSsEBwejU6dO6N27tyiNpXEQTz/9NOLj49G1a1dERUVh\n3LhxorSW7JbKl9+vqqrCBx98gODgYDRq1AgHDhzAqlWrJK9btGgRpk2bhgYNGmDLli0AgNq1a2Ps\n2LHIzc3F2LFjZX1HhGejYXJiYoJwQVJSUrB69WocOHBAbVM8hjfffBM5OTlYt26d2qYQLgC1QRAE\nAQC4efMm1qxZg/Xr16ttCuEiUBUT4ba42nQW7sxnn32Gli1bIiEhAbGxsWqbQ7gIVMVEEARBSEIR\nBEEQBCGJ27dBUBUDQRCEbVirQPKICIJxU4bU+L/XX39ddRtc5Y+eBT0LehaW/+TgEQJBEARBOB4S\nCIIgCEISEggPIi4uTm0TXAZ6FgboWRigZ6EMt+/mam31L4IgCMIUOb6TIgiCIAhCEhIIgiAIQhIS\nCIIgCEISEgiCIAhCEhIIgiAIQhISCIIgCEISEgiCIAhCEhIIgiAIQhISCIIgCEISEggHsXYtcOGC\n2lYQBEE4DhIIB/HUU8C776pthTKKi4EePdS2giAIV4UEogZz7Rpw4oTt1//nP0D37o6zhyAI14IE\nwoG425yB9i7Gt2sXkJXlGFsIgnA9SCAcSE0TCFrtlSA8GxIIB1JVpbYFBEEQjoMEwkPJzLTevkAR\nAEEQlvBR2wDCOcTEALVrAyUl5tNQFRNBEJagCMKBuFobhKvZQxCEe0ECQRAEQUhCAuHBUARBEIQ9\nkEAQNkNtEATh2ZBAOBBXe2O3Zg85eIIgLKGaQKSlpaF9+/Zo164dlixZIpkmIyMDkZGR6NSpE+Li\n4qrXQBenqgrYt09tKwiC8GRU6eaq0+kwe/Zs7N27F8HBwYiOjkZiYiIiIiL0aW7fvo1Zs2bh22+/\nRUhICAoLC9UwVRHVGUH8/DMweLDrRS0EQXgOqkQQmZmZCAsLQ2hoKHx9fTFp0iRs375dlOaLL77A\nuHHjEBISAgBo3LixGqa6LDRqmyAIZ6NKBJGXl4cWLVro90NCQnDkyBFRmpycHFRUVGDgwIG4d+8e\nnn/+eTzxxBOS+S1atEi/HRcXVyOqo+S0Hzg7uqA2DIJwHzIyMpCRkaHoGlUEQiPDs1RUVODEiRP4\n/vvvUVxcjN69e6NXr15o166dSVqhQBDyIQdPEDUH45fnxYsXW71GFYEIDg6GVqvV72u1Wn1VEk+L\nFi3QuHFj1KlTB3Xq1EH//v1x8uRJSYFwFaqzPcAVIgiCIDwbVdogoqKikJOTg9zcXJSXlyM1NRWJ\niYmiNKNHj8ZPP/0EnU6H4uJiHDlyBB06dFDDXMIMJEAE4dmoEkH4+Phg5cqViI+Ph06nw4wZMxAR\nEYHk5GQAQFJSEtq3b4/hw4ejS5cu8PLywtNPP00CQRAEUY1oGHPv90CNRgNXuAWNBnjiCWDduuop\n79AhoG9f82/xGg3g7Q1UVprPQ6sFWra0PRIYPRrYsYMiCYJwR+T4ThpJ7UBczVHSSGqCIOyBBIIg\nCIKQhASiGmHMcVEGvf0TBOFsSCCqkaVLAS964gRBuAnkrhyIteggK8txZVEEQRCEsyGBqEZczanz\n9rha4zpBEK4BCYQDcTdH6272EgRRvZBAuClyohG5EQsJBUEQUpBAEARBEJKQQLgpjmjP4CMHiiAI\ngpCCBMKBVKejJadOEISzIYGoRlytFxNFEARBWIIEgiCBIAhCEhIID8bVIhaCINwLEggHUp2zp7pC\nIzUJEEF4NiQQBEEQhCQkEB6M3MiA2iAIgpCCBMIN0ekckw/1YiIIwhIkEA6kuhytjw9w7pz1dNRG\nQBCEPZBAuCmFhY7LiyIIgiCkIIFwUxzh1EkYCIKwBAmEm+JI505CQRCEFCQQDuDxx7lPV3a0n34K\nrFghPkaN1ARBWEI1gUhLS0P79u3Rrl07LFmyxOR8RkYG6tevj8jISERGRuKtt95SwUp5bNwoL52a\nb/1z5gDPP++48gmC8Hx81ChUp9Nh9uzZ2Lt3L4KDgxEdHY3ExERERESI0g0YMAA7duxQw0SbcLXZ\nXIW9mCz1aKIIgiAIKVSJIDIzMxEWFobQ0FD4+vpi0qRJ2L59u0k6Rp7LYUgJBD1egiAsoUoEkZeX\nhxYtWuj3Q0JCcOTIEVEajUaDQ4cOoWvXrggODsayZcvQoUMHyfwWLVqk346Li0NcXJwzzHZrKIIg\niJpNRkYGMjIyFF2jikBoZIzg6t69O7RaLfz8/LBnzx6MGTMGZ8+elUwrFIiagiMHwZFAEITnY/zy\nvHjxYqvXqFLFFBwcDK1Wq9/XarUICQkRpalXrx78/PwAAAkJCaioqMDNmzer1U6luFobhBCqYiII\nQimqCERUVBRycnKQm5uL8vJypKamIjExUZTm+vXr+jaIzMxMMMbQsGFDNcz1eEgoCIKQQpUqJh8f\nH6xcuRLx8fHQ6XSYMWMGIiIikJycDABISkrCli1bsGrVKvj4+MDPzw+bN29Ww1S3pqLCsE0RBEEQ\nSlFFIACu2ighIUF0LCkpSb89a9YszJo1q7rNcipqOeQ7d4D7982fJ6EgCEIKGkntQNRytGVlwMmT\n5s8vW2b5ehIIgiCkIIFwU4RVRh9/DHTrpjwPEgaCICxBAlGNOMshl5TYdz0JBUEQUpBAuCmWnPqN\nG+J9WjiIIAhbIIFwIFJO+/ZtICbGueUaC0DTpvKus3c2VxIegvBsSCCczPnzQGam4/OlkdQEQTgb\nEggnUx1v2a++avm8OQEgYSAIwhIkEE7GHaphSCgIgpCCBMKBSDladxAIgiAIKUggnIwrCwQtOUoQ\nhCWsTrWRkpIia3pugFvgZ/r06fba5LZYc7RqOWISAIIgbMGqQDRo0ACxsbFo1KiR1cykVoWr6bhy\nBMFDAkIQhBRWBWL06NHo3LkzwsLCEBAQgOjoaMTExCAyMhI///wzCgoKMG7cOH1aQoyzBMIRTp2q\nmAiCsISs2Vy3bt2Kdu3aobi4GO+88w727duHDz/8EEVFRWjTpo1eIAhTnCUQSvIlASAIwhZkCUS7\ndu0AAH5+fggLC8O0adMAAOXl5VStJEDKEbuyc6YIgiAISyheD8LX1xfTp09HYmIiwsPDceXKFWfY\nRRAEQaiMYoGYPHkyevTogQ0bNmD//v2YOnWqM+zyGFyhkdpVe1cRBOHa2LSiXHh4ON58801H2+KR\nOMv5OqJ6iKqYCIKwhOKBcp9//jkOHz6M8vJyHDx4EFu2bHGGXW4JvakTBOFJKI4gCgoK8MMPP2DF\nihW4d+8e2rZti/HjxzvDNsICjnz7p+m+CYKQQrFAhISE6NsdqBeTe+Cs2VwpIiIIz0ZxFRPfi2nr\n1q3IycmhXkwqYatz/vlnIC/PMXkRBOHZKBaIkJAQLFiwAFlZWfjkk08QGxvrDLvcEjUcrdIy+/QB\nnnxSfC0JBEEQUigWiH//+98IDQ3Fm2++iY8//hjR0dE2FZyWlob27dujXbt2WLJkidl0R48ehY+P\nD7Zu3WpTOa6EWgJCAkAQhC0oFojAwED88MMPqKiosLlQnU6H2bNnIy0tDdnZ2di0aRNOnz4tme6l\nl17C8OHDwdzAy1XnSGp73v6Nr6FGaoIgpLBJII4ePYoJEyZgxIgReNXaepcSZGZmIiwsDKGhofD1\n9cWkSZMkG7s//vhjjB8/Hk2aNFFchhrs3Al88onaVoix5PzdQHMJglARxb2YRo4ciSZNmmDhwoVg\njOHy5cuKC83Ly0OLFi30+yEhIThy5IhJmu3bt2Pfvn04evSoxTUpFi1apN+Oi4tDXFycYpscxXPP\ncWtE/+1v1teKtgclEYS1iIGEgiA8n4yMDGRkZCi6xqpAnDlzBl5eXvoJ+4SN0hqNBq1atVJm5V/X\nWWPu3Ll49913odFowBizWMUkFAhXoLAQOHhQbSs45LRBkEAQhOdj/PK8ePFiq9dYFYi2bdsiIyMD\n6enp8PLyQnR0NKKiouwyNDg4GFqtVr+v1WoREhIiSnP8+HFMmjQJAFBYWIg9e/bA19cXiYmJdpXt\nKTiiDYKEgSAIS1gVCB8fHwwZMgRDhgwBwLUfrFq1ClVVVQgPD0dcXBx8fJTVVEVFRSEnJwe5ublo\n3rw5UlNTsWnTJlGaCxcu6LeffPJJjBo1yq3EwVWm/paKIKiKiSAIOShug+jZsyd69uwJgKt+Wr16\nNcrLyxEcHIz4+Hj4+/tbL9THBytXrkR8fDx0Oh1mzJiBiIgIJCcnAwCSkpKUmuVyONvpys3fUhUT\nCQNBEJawaTZXnvDwcISHhwMArl69ip07d2LixImyrk1ISEBCQoLomDlhWLt2rT1mqkJ1dQFVs5sr\nz7PPAu+8AzRoYF8+BEG4Foq7ud6/fx/Xr183Od68eXPZ4uDJ8MLgKmMEzEUQu3cDpaWGNPaQnAwY\ndUIjCMIDUBxBbNiwAbVq1cLWrVvRuHFjTJgwAcOHD3eGbW6JRiN2uK4wUE4qzcMPc11xHYUd4yYJ\ngnBRFEcQderUQYcOHXDz5k2sWbMGd+/edYZdbourVS1ZSldVpSwvS1RW2p8HQRCuhWKB6N69OzZv\n3owVK1YgJSUFleQZRFR3FZOtEYTcawmCqLkormLq1KkTli9fDgD4888/0bRpU4cb5UmoPebAUjdX\nR0YQN25w+bhK2wtBEPZjVy+moUOHOsoOj8Hrr5js0CGgvFwsEI4UCUdMteFIgUhKAgICgL/GNhIE\n4QEormIixNy5I97n36Dv3gXWrat+e4ypzsn6Cgocmx9BEOoiSyCKiooAABUVFdDpdE41yN1o08b8\nucpK9auYLJXtTNvKyoDcXMfnSxBE9WFVIN577z288cYbmDdvHu7cuYNnn322OuxyG27eFO8b18Gr\n3c3VUtUWX8XkaJsA4K23gNatHZs/QRDVi9U2iJiYGMTExMDX1xepqamocrRX8WCqYzyEEhuMj9nb\nBmGpQdpYOAmCcD+sRhD+/v5ISUmBt7c3Jk+ejP79+1eHXW6LIyKIGzeAq1ctp+Hz/egj5fnz2Kv1\n1E2WIDwbqxFEVFSUaHrvadOm6bdPnTqFzp07y1rfoaYgfBTC6h0lvZhiY4ELFyyPTubzWrjQcl5y\nJutzlKMnwSAIz0JxL6Z169Zh7ty5SElJgb+/v8k03TUdc1qpxHneuOHYkcnmurk6s5Ga3hkIwv2x\nqZvra6+9hqZNm2Lp0qXIyclxtE1ujbkIQglednY+HjRIng2OFgaKIAjCs1A8UK5x48Z44IEHMGLE\nCIwYMcIZNnkUtryly3n7tpRfYKD8tHLOm8OSnRRBEIT7o/hdNS0tDSNHjsS4ceOwZMkSZGZmOsMu\nt8URjdSOdK6WejFZsq2gAHj7bUDJsBeKIAjCs1AcQcTFxWHFihUoLi7GsWPHcOzYMf0Kc4RpFZNw\nW64DtTeCkJvWklA8+CD3OWMG0KyZvHKEdlMEQRDuj2KB0Gg0OHr0KKKjo9G/f3/q9moFR0cQSvOz\ntxcTRQUEUXNRLBA//PADAOCNN95A7dq1MWDAAMyePdvhhrkr5qqYqrMNQm5aWyb602iA7GwgIsI0\nLUUNBOFZKBaIcePGQaPRIDY2FiUlJfj999+dYZfb4ohuro4UCDltEEojiGvXpAWCIAjPwmoj9fHj\nx0X7/fr1Q2xsLABudTnhIDrjtDUROY3U9oxxUBqR2NpILed6S8cpmiAI98dqBLFnzx789ttvsjLT\narXo0aOH3Ua5M3KqmJKTgVmz7CtHyVu/Pd1cqX2CIGouVgXilVdeqQ47PBJzYmG8hoS166TykOu4\n5fSeUioC5tJT1EAQnoVqCwalpaWhffv2aNeuHZYsWWJyfvv27ejatSsiIyPRo0cP7Nu3TwUrlSMn\ngrDmSKurkVrOZH2WyiFBIAjPRhWB0Ol0mD17NtLS0pCdnY1Nmzbh9OnTojRDhgzByZMnkZWVhZSU\nFDzzzDNqmKoYOVNtWHPu1RVBCPMqKgLy8kzTHD5s2VZzkHgQhPujikBkZmYiLCwMoaGh8PX1xaRJ\nk7B9+3ZRGn9/f/12UVERGjduXN1m2oQjurmqwcyZQEiI6fEPPjA95ur3QhCEY1DczRUASktLodFo\nUKtWLZsKzcvLQ4sWLfT7ISEhOHLkiEm6bdu2YcGCBbh27RrS09PN5rdo0SL9dlxcHOLi4myyyxGY\nG01cnRPjWYsgpLq5FhZK5yU11Qa1QRCE+5GRkYGMjAxF18gSiKqqKmzbtg2bNm3CoUOHUFVVBcYY\nvL290bt3b0yZMgVjxoyRvS6E3HRjxozBmDFjcODAATzxxBM4c+aMZDqhQLgaalQxWStPSiDMlSl1\nnCIIgnA/jF+eFy9ebPUaWVVMcXFxOH78OObPn48LFy7g2rVryM/Px4ULFzB//nwcPXoUAwYMkG1o\ncHAwtFqtfl+r1SJEqn7jL/r164fKykr8+eefsstQi+qqYnJkGwRg/xTjxlA0QRDuj6wI4rvvvtNX\nJ+l0OjDG9FVMvXr1Qq9evVBWVia70KioKOTk5CA3NxfNmzdHamqqycJD58+fR5s2baDRaHDixAkA\nQKNGjWSX4cpUZwQhR0icEUFQlEEQ7o8sgRC2NQwZMgSDBw9G69atERAQgFGjRpmksVqojw9WrlyJ\n+Ph46HQ6zJgxAxEREUhOTgYAJCUl4euvv8a6devg6+uLunXrYvPmzUruSzUsRRBSTrOgANiwAZg3\nT1k5jhjAZuvIZ2qDIIiageJG6v379+u3f/zxR8ydOxcffvih4oITEhKQkJAgOpaUlKTf/sc//oF/\n/OMfivNVG6XrQWzaBLzwgnyBcEQ311On5NvI38/du0Dt2vJsJAjCM7Cp5vnChQv46aef0LFjR3z9\n9deOtsmtcbXJ+qTSlpSIj8sRm/r1AYF+Wy2HogmCcH9sEohmzZqhsLAQzz//PBYuXOhom9waZzdS\n2xJB2IPwfvixjOby9Pa2ryyCIFwLxQJx7Ngx+Pn5YcyYMVi/fj1WrlzpDLs8Ao3G8QsG8Thyqg1L\njdTCa/mhKnLaIKiRmiDcH8VtEMHBwdi2bRvKy8vxxx9/YPjw4c6wy22x5Gira1S1Ld1cHQFVKxGE\nZyFLIPhurQAQFBSEMWPGWExTk5EzF5OSPIzh87t8WX5+9szm6iP4hfTpAxw6ZD69cCwF/RQIwv2R\nPVBu6dKlOHv2rMm5M2fOYMmSJYoGynkKpaWmx4SOsaQE2LWL21bSNVSOc/3mG/PnbJmsz1yaKVMM\n2927m+YvxNGD7QiCUBdZEUR6ejo2btyIWbNm4bfffkO9evXAGENRURE6deqEKVOmYO/evc621eW4\nds30mNC5v/ii9TyURhiOrBaSk5cwguC3qQ2CIGoGsgfKPfXUU3jqqaeg0+lQWFgIjUaDxo0bw6sG\nvzYqufXqcJjr1wMdO9q2YJCcRurdu7lPJaOuCYJwX2S5uMzMTFz763XZ29sbaWlpmDlzJubOnYub\nN2861UBXRkn1kNQYgevXgT175OdhnI8xU6dyA+4c2UgtTCNRwyiC2iAIwrOQJRBJSUn6qTR+/PFH\nvPzyy5g2bRoCAgLcZiEfZ6C0/cDYIS9aBHz7rfhYSQmgYForq2WYOwaIu7kqyc8cNTiYJAiPRPZ0\n3w0bNgQApKamIikpCePGjcO4cePQtWtXpxroyihxiFIN2lJERQFXrpg/r/St396J9RgDvv9eXnpq\ngyAIz0KWi9PpdKioqAAA7N27FwMHDtSfq6ysdI5lboCSCGL+fHl5Zmfbbg9g+wC6q1e5z59/Nk3z\nwgvy8qNqJYLwLGQJxGOPPYYBAwYgMTERfn5+6NevHwAgJycHgYGBTjXQlVEiENZ6PElx8KD0MqDW\nsKWRml85bu1a03O+vvLKpTYIgvAsZFUxLVy4EIMGDUJ+fj6GDRum77nEGMPHH3/sVAPdjfPnpY/b\nUuVy6BCQl2d/PtbaIADDPErGS4wqEQiNhpuOIzpauY0EQbgesqfa6N27t8mxhx56yKHGuBtKnLXQ\nGfNv19besm1p9DWe/0nuQDneFimB8PGRvk4qv169gBo4JIYgPBLqd2IHzm6ItWU1NyW9mOSkkTp+\n/rxhTIRU2vJyaqQmCE+ABMIObHWCciMIW5Hbi0nOVBtS5154AXj4Ycv5EQTh/pBA2IHSHkOOcJy2\nRANK5mKyNQIRotGYit+JE8C5c8ryIQhCXRRP900YcORiPM5CrjDxbSTCthL+eiVlmaNHD6B1a+DC\nBfn5EQShLhRB2IEaVSmOHCgnJ4JQEvlYK5eqngjCvaAIopqwJVqw5ZqCAqBBA/ExOQ3Q5qbdEI6R\nsAZ/7YgRgL+/vGsIgnBdSCDswBWrmM6cEe/LjSAsVTG1bWtYbtQSwrLu37d8niAI14eqmOzAVauY\n5F4jJRCMAffuGdLk5wPBwcrLtGZHVRVw6pRj8iUIwjmoJhBpaWlo37492rVrhyVLlpic37hxI7p2\n7YouXbqgb9++OOWC3sQVIwhj5LYh8FNqVVWJq5Tefx9YulT6GmP7lTyPHTuAGjzPI0G4BapUMel0\nOsyePRt79+5FcHAwoqOjkZiYiIiICH2aNm3a4Mcff0T9+vWRlpaGZ555BocPH1bDXLMocYjCSfDs\nEQZnrCjHmEEg7LFFySC+khLl5REEUb2oEkFkZmYiLCwMoaGh8PX1xaRJk7B9+3ZRmt69e6N+/foA\ngJiYGFw+CkK8AAAgAElEQVSxNAe2SrhDnbqlCELY3tC4seGYrQImVc6NG9Ln3eHZEURNR5UIIi8v\nDy1atNDvh4SE4IiFVtDVq1djxIgRZs8vWrRIvx0XF4e4uDhHmGkVV5xqQwrjhmepPBMSgF9+sU8g\npLhyBWjSRLlNBEE4loyMDGRkZCi6RhWB0CjwQPv378eaNWtw8OBBs2mEAlGduMNbsNzJ+hzxdi91\nnVAIKIIgCPUwfnlevHix1WtUEYjg4GBotVr9vlarRYjEwgenTp3C008/jbS0NDQw7tzvArhDL6bS\nUvNv61IO254pQawJRF4et+/lRREEQbgDqrRBREVFIScnB7m5uSgvL0dqaioSExNFaS5fvoyxY8di\nw4YNCAsLU8NMq1RnFdOECebXmrDEokXyqpj4e6mqst15WxMIwLAGNwkEQbg+qgiEj48PVq5cifj4\neHTo0AETJ05EREQEkpOTkZycDAB44403cOvWLTz33HOIjIxEz5491TDVIjIiNLsQOtyvvgLS0pSL\n0o0b5kdCS42krqqSX4YtbRXl5eLyHEFWFjBunOPyIwiCQ7WR1AkJCUhISBAdS0pK0m9//vnn+Pzz\nz6vbLEVs3ly95Slx3jzCQXDGHD1qSOOsKqbqYPt2YOtWdcomCE+GRlKrwCuvyEtn/IZuy1u3l5f1\nuZSMR1Lb6uil7DM3VsKRYmLLynsEQViH5mJSAVurV3Q6sWPt1An47TfL13h5Gap1LGFLG4Tx4Lqb\nN61fU1UFTJoEnDwprww5VMeIdIKoidC7l4rY69jatpVXhpJGaiURhNHYRrz2mrzrUlOBP/6Ql1YO\nJBAE4RwognBhvvlGvG/svOVUrZw9C1y9aj2dI6qY5OCMvEkgCMI5UAThwvzwg+kxpQIhRxwc1Ugt\nBxIIgnAfSCDcCGPn+vXXyvOQ6i28ciWwc6ehDGdMCGhu3xGQQBCEc6AqJjdDuFaDLfj6mh7jB68B\n8toslJCeDvz3v47LTwoSCIJwDiQQbgRjQHi4fXlICYQQLy/HvuV/9hk3xYYzIYEgCOdAVUweTpcu\n4n1rAtGpk2MFgqbUIAj3hQTCjbDFcXt7i/cfeMB82iZNAH9/xwqEtUF6joAiCIJwDiQQKrFnj/Jr\nbHHcxg7aUgRx4wbwxhvVG0GcPg2UldlXBgkEQTgHEgiVsLD+kVmUOm6pBmdrVUwA0KaN6bH33lNW\nNo81gejQAVi2zLa8eUggCMI5kEB4MBoN4OcnPiZHIKQIDLRcPWUOOW0Q9vbMIoEgCOdAAuFCWIsQ\njKe2ePddy+k1GqBpU2DYMMMxWwXC29s5y50SBOG6kECoiNLZWg8fVp5/VZX4zd8egbDF2VMjNUG4\nLyQQKrJxo3hfqQO25hg1Gs5BC6fksFUgfHxsEwil19y8aX2GWmNIIAjCOZBAqMiNG+J9pc7UWpWP\nlEDY0o4A2F7FpDSCmDUL6NxZ2TW8QDz1lLLrCIKwDAmEC2HOAR86ZFt+Xl7cmg3CN2x7qphsQY7o\nCe2Ts3aFuevXrlV+LUEQ5iGBcCHMOVPBSqw25SlVxWQ8lbg1nCkQQmxZHY6qmAjCOZBAOIH/+z9g\nwgTl15lzpuaO29IGwW8rdcTVJRC2OHu512Rnq7duNkG4IyQQTsIWR2fOmWZn226DsUB89BH3qVQg\nnLnuc3U47StXgI4dgaNHnV8WQXgKJBAuhKPHDHh5cQIhFKuiIsM5JdgaQSjFGRHExYtAixbcdmmp\n8vwJoqZCAuEENBrb3oqd8SZtHEHUqsV9upJAKF0lzxhrAmFLw7eQBx8Etm2zLw+CcEdUE4i0tDS0\nb98e7dq1w5IlS0zO//HHH+jduzdq166N999/XwUL5VOnDveZmWl7Hrt2OT6CkKpiWr/ecE4J7iwQ\nQtttEeGCAuDHH5VfRxDujioCodPpMHv2bKSlpSE7OxubNm3C6dOnRWkaNWqEjz/+GPPnz1fDREWM\nGsV9Rkdzn7t2Kc9j5EjHRxBSVUxNmxrOKaE6BIIx5zZS2wNNGULURFQRiMzMTISFhSE0NBS+vr6Y\nNGkSthtNNNSkSRNERUXB19aO+05GOCgrMVF8LjfXtjxtma3V2nlXq2K6csX0GH/fISGmo8sdja0i\nTAJB1ERUWXI0Ly8PLfhWQwAhISE4cuSIzfktWrRIvx0XF4e4uDg7rJOHcFCWlPOU44jatgXOn1d2\njdIyzI2klhKIZcsA44AtJIRz6uYEwstLmfOcN8/0GH8fV6/Kz0eIHKG0F+oeS7g7GRkZyMjIUHSN\nKgKhcXCdgFAg1MDW2zF2iM7oxVRVJT2SWkog6tY1PcYLgzmB4PN+6SVAoilJFvY6X2vPTZi/rWWR\nQBDujvHL8+LFi61eo0oVU3BwMLRarX5fq9UiJCREDVOcQlCQvHQlJeL9VascawffBiE1klpKICw5\nWmsiWFmp3D4lVFSYP2fNeQvviwSCIOSjikBERUUhJycHubm5KC8vR2pqKhKNK/L/grnhf2bDhobt\njh2lV2iT4o03HGsHPxeTlEBIOXwpgZD7+C05cGtIlXH9uniA4AMPAAcOyL9eiPC+bI32qA2CqImo\nUsXk4+ODlStXIj4+HjqdDjNmzEBERASSk5MBAElJScjPz0d0dDTu3r0LLy8vfPTRR8jOzkZdqXqQ\nakaOQ+LTNGtme926vUhVMVlqbJa6rw8/BMaONX/PfN72CISU833sMWD/frFdgqBThBKBsBU3fE8h\nCLtRRSAAICEhAQkJCaJjSYJZ6Zo1ayaqhnIlrFWnGDtkZzkXa/lKVTFZ6r0k5UgfecRyGfy9Sj0T\nb2/bFwySGtxmznZrAuCIRYtIIIiaCI2ktoGyMsvnhY7MWCA2bXKOTebsMK5iUiIQwi6ptkQQPjJf\nPxgDjh+XzleIOduVtkHodIDRu4kkV68CK1aY5kEQNQUSCBswFghjZ2ZJIHr3dpwd1urTpaqYeNsY\nA86eFac3drTBwYZtYwfZtq3YBqkIQu4Qlqoq4IUXrKczvl/GuEWXlFYxFRcDaWnWy1uzBnj+eUNZ\nBFHTIIGwAePqD6EDat4c6NVL3AZh71QS5rCniokxoF07+fkZt10YTxtuTwSxYYO08zfG+Nlt2MCN\nDLf2dm/u/PXrlq+zd4oOgnB3SCBswDiCEDqPy5fF3VX56bV5HDkEhHfAAQHS55W2QViyTTCuUZSP\nI6qY7tyR103W2D6+8d+WKiYA+PRTw3GtlrNDiPBZURUTURMhgbABSxGEt7fYsfj5iR2YI2cOad6c\n+/zXv6TPS7VB8BMLSmFOIBgTVzfxeQs/pRy8EjE0bkgWPmP++Wk04me9d6/4vDmMBYLfFwpCy5bA\n5Mni64T2UwRB1ERIIGzAOIJQMpLXUQJRUABMmmQ5jXEbxLZtQL165tObi0QsIaeba5Mm1vMxXqdB\nuLAPLxaVlZwAnzjB7fMCIfX8//wTiIoyPV9VZRAjfpJgviG6oECch7UR2ImJjh/cSBCuBAmEDRhH\nEFLOw5xzkVvtYo0mTcRvuI8+aprGy4uzlU/n52c+v5wcYNo0+eXLqWLiz8mZCeX+ffPn+OfNl3H5\nsvi81PM/e9bQM0oYncTHA99/L07788/S+Qj3pUTof/8DvvjCvN0E4e6QQNiApTYIKeLjgR49uG1n\nTE7LGLB5s+lx3on/+ad4n79GSFiYshlb+bTGAiGspuGjAjkN88bTjggRRhDCTx7hvfDTm/Nl9ujB\nzRMlxPitn78XSwJBVUxETYQEwgYstUFI8Z//AMeOcduOiiCEGK+jcPs298k7yfJy4J13xF1s7W0s\n5683boN46CFDGmvjRYRYiiD4fHgRKiwUnxc+f/674Y+dOAEcOiROb7z4Dy8QVVXcmh6rV3M90Rwx\nhxNBuDMkEDagtA2C5+BB5RFEmzamPYikEDr8+vW5T96R+vgAL78srmKyVahmzOA+jauYeIEQLs3J\nV+3ImYbDkkDcvSvO57nnDGtrA2LnzadRMnkgfw9lZZyQb98OHDkC3LsnXYaQ6lqrmyDUgATCBuQI\nhJRD6dNHeVn79wP+/pbTmKvCyc+XPt6sGVelBIgnFuRp3x746Sfpa195RVym8TgIYX0/76SlprrY\nulW8byna4BuPhaJgTiD+ms7LpnWo+UUNebuFNlkbSU4QnggJhA3IaaS2B34JUx5rb+BSAmHOgQLA\ntWuGpUe1WtMeRI0bA337SpdlHHkYt0FI2SL1Nm9tjichvNC9+KLhWEWFoSzhLK9Ll3KfxcXm82vZ\n0nJ5vL1SXW2NXwbMifOKFaZtHwThbpBA2ICcRmp7RGPHDuDZZ7ltf3+xQERFAbNmidNLOSlrUQeP\nn59hGVI5dvHjIfj7M26DkBqUx58zJzrWkIqEWrY0OGvheT5a4SMdKYyfzblz4n3+eUtFEN7ewMWL\nhuPmBOK997g/Z3D3LrB7t3PyJgghJBBmOHHC8JZtjPDNsmVL6XS3btlX/qpVwM2bQKNGYoFo3x5Y\nuVKc1lovIUdFOKNGGSIGY4GQiiD4MReVlVx6fryBUqxNifHrr4btmze5z1OnzKcvLeVEkV+n4+BB\n8XmpCOLAAYOQCO0x9+wdOaWKkHPnuPEbDz/snPwJQggJhBmOHuUmgpOirAxo0IDbvnQJGDPG0HOI\n54cf7LeBL0NYRSPl7M3Vg/PdOZUKhJIGbH6Na14ghLbwjeJy14oYPFj6uLmR4rZSUsLZZq7dg3/e\nJ08ajl27BkyZwm2PHs2NGwHMC4Gz2ibateN6pBFEdUACYQZLTrW8XOwYNBpDzyEe43176NwZCA83\nf95cnTpfTeUMgeDz3L8f+P13ru5/xQqxY2zcmPvkHa41p8mLjbMpLeWqmYzbXngOH+Y+jaMQvgda\nQQGQns5tOytS4Nm3z/T7s2dxJoJQAgmEDZSVWXcM48YBgvXBrfLoo4C5Zbl37wZ++YXbNnaiJSXA\nsGGW81YqEHK6bvJ5tm4NdOjA2T9njkEMLlzg9qUw9+zktoXYS0mJZYEwh1DgjMeB6HTA3//OzTAL\niJ95Zqa404AxwkiFr47j8xg82P7qSsbE1XAEIRcSCDNYetstLwf69+fe7M2xerVhyUw5jB8PTJgg\nfa5WLaB2bcO2EP44YNp1lMcZAmFu7MeAAUC3bpxw8GMmjO0wNxbEuNw33uDycjRlZVwVU2kpMHWq\n/OuEvwnj+8/P55ZnfeIJbp9fDHHtWiAmhmuPuXDBMH8Uz9Wr3D3y03/4+nKiU1pqqAIrL+fstLR0\nbViY6RQkPIcPA126yLtHghBCAmEGqbfc0lKuaqGsjPuHs9QQakt5CQncCF5LtG9v/py5yfaUDuaS\nU8VkLs0HHwBZWdy28TM0FojISGDgQMN5466pr75qvqOAMZbmmZKiVi3urX/9evnXCLvT8tEH35At\njP6Egrxnj2F7+nRg6FBxnnyvsOHDxasN3rtneB4lJZyd334rbdf+/cD589xzf+0185HRjRumK/dZ\n4s4dy92FCc+HBMIMUk510yZuXqWffrI8bbZcHnrI0F3RywsYMsQwcZwUd+4Af/ub+fODBgG5uabH\nlY6atiYoL78snlLDEgkJwMiR3DY/qytfx3/ihPjNlu8dFBgo31aeZs2Upbd3BDS/Ip3UgDx+tT1A\n/Oz5CECq+2tlpXgeq/v3DY6er54y16g+aBD3WVoKvPkm8Mcf4vN8m8WMGYYZbqXIyRFXhbVpw81Y\nS9RcSCDMwFchCHsQ8dNB7N/PdT+1l1q1DGsjy5mCIyDActWXRgO0aiU+lpwMLFigzC5r4vfOO/IF\nYvduwxxQLVtyb9cdOxrOC0dy8+0rAwaY5jNvnuVy5NbT82MgrE2PYk1A+CqhjAzTvITjJIRRwfnz\n3OdLL3EN+8YLFAm5dcvQU4oXUanIQNhgzfe6Mx4nw0cBv/8uXZZGw0VHDz1kWGIV4LoMZ2dz20eO\ncONgli8HHnzQvN0AF5lRQ7pnQAJhhqef5j6F/5TCGUcdIRDCxmVnzPIKAM88I9+Z8wQFWU+zcCHX\n9dNeXn4ZuHKFmzdq+3Zg8WKuOiUvjzvP9wbj124wpnt37nPQIGD2bG578WLz5fFVUcJ5lnjGjjVs\nK/k+jMXE2khtAOjUyfIcW927m3Zy4KvueD7/HJg717DPdwo4dIgTrdu3uSqn337jjl+4YL68/v25\nT+Ou3fx3PGUK17338GHD1CeMSVdBPf00EBFhvizCjWAqsWfPHhYeHs7CwsLYu+++K5lmzpw5LCws\njHXp0oWdOHFCMo2zboH7+TNWWMjtl5cbjgGMHThge96DBzO2YIG4rO++s89exhjbv3+/3XmcO8dY\nSYn9tjiKP/9kLDub2/79d8Z69xZ/D4xxn2PGMLZuHbc9ezZjwH6Wnc3Ys89yx+LiuM8HH+Q+a9Uy\n5PHFF4y99x5j9+4ZjrVpIy5H6m/gQMaCgsTHoqMZGzvW+rXO/rt+nbF//5vf329ynufECfHxhATu\n+x8+3HBszhzD9oQJ3GdWFmOffcZtl5WJv7POncVlMMbY8eOM6XSMFRUxlpJi+TuvqmKsooKx4mLG\nRo5kbN48+35DQhzxP+IIKitNn1t1I8d3qiIQlZWVrG3btuzixYusvLycde3alWXzXuAvdu3axRIS\nEhhjjB0+fJjFxMRI5gVA78Rt5dIlxrp3536UjDF25IjpP9Px4+JjRuYqorKS+2fhGTGCsYIC2/Pj\nef311+3PxA345RdODBo35vYBxiZPZmz3bm67f3/GgNcZY4wdPcody89nLDiYscREU2fKU1ZmONa2\nrThNVBT3KfxtPPmkOE1FBWP//a99jp13ro79e93kWGiodNrERE74zOX1wAPSx8eP5z7XreNEEuBE\nV6fjHD7A2K5djH3zDbf9xRfc/8GePYxptYbv4PRp7uXpwQcZ+/pr8bMVEhfHfadlZVz+a9cydvUq\nd+7WLcb+7/8Yy8w0/e3w/yPXr5vmaczVq5ygWaKqyvRYSYn4eFmZ+P+dMU70+N+vNYqLpcuxF5cV\niEOHDrH4+Hj9/jvvvMPeeecdUZqkpCS2efNm/X54eDjLz883yQsAe+ABxk6eZOytt7gv9cYNxgID\nGdu4kbFt2xjbsoWx3FzGSksN1xUVcU45PV38Qw8JMf3xv/SSYfuTT7jPmzcd/1zspaYIhDHZ2Yzd\nvs39E547x9ihQ4yNHv06Y4z7x7pxg0tXXMz9s86bx1j9+lxUeP++OK+iIu77bdiQ2z97lrHffuOu\nzc3ljv38M5dm61YunVBoCgoM+2++yX0+9xz3Rv7II4x9+y1jTZuKf1/z53OfjRpxeWzYwFizZowN\nG8bY3r2MxcdzkawcMZB24K+zU6ecITzy/sLCrKd54gnGdu4UH3vjDdN0wshv0CDGvLwYa93acCw2\nVpw+IIDLG2Ds8GHGOnZ8nU2caDjfrBn3/Qwdytjq1Yx17MjYrFncM+fTrF7N2PLlnMB99x0noIcP\nM3bsmOF7/vJL7jd46xZ3bMgQxj76iLG//53b79aNi7r27uVecJo3547PnMnlO3QoY5Mmcb+BV17h\norP33+dEDmDs8ce5+0hOZmzfPi5vrZa79vRpxs6c4SLGjz5i7O5d7mVp3jxOkE+dYiw1lfut37vH\n/cZeftmFBeKrr75iM2fO1O+vX7+ezZ49W5Rm5MiR7ODBg/r9wYMHs2PHjpnkBcDkR2T8Dyj8Cwpi\nrF496z/Ypk0Zy8kRH9u8mXMqr73mvGdjDzVVIKSw9Cx0OvHLgjHTpnERiVwuXWJM8FNlFRVcdRhj\npgLEGCdgjRsztnAhY5cvc8fS0jjhsUZZGWN37nCRxrJljE2fztiLL3Ll/PEH5zD++U/OEb34Iud0\n+/d/nTHGOYszZxh7/nnGPviAczr/+Adnx6+/GsTt8GFOaEeO5Mrp359z8j//zFiDBlyaVq24qqdx\n4xjr0MHwP6LRcM4vJoZzdLw4PP64OM2jj3LO2dr/YePGtomStzcXmUuJpRoi6eVVveX5+MhJ56IC\nsWXLFlkC8dNPP+n3Bw8ezI4fP26SFycQ9Ed/9Ed/9Kf0zxpOWADTOsHBwdDyQ00BaLVahBjNM2Gc\n5sqVKwjmRxUJ4DSCIAiCcDSqdHONiopCTk4OcnNzUV5ejtTUVCQajchJTEzEunXrAACHDx9GYGAg\nHrTWAZsgCIJwGKpEED4+Pli5ciXi4+Oh0+kwY8YMREREIPmv9SKTkpIwYsQI7N69G2FhYfD398fa\ntWvVMJUgCKLGomFuWkeTlpaGuXPnQqfTYebMmXipBq/v+NRTT2HXrl1o2rQpfq3B03ZqtVpMnToV\nBQUF0Gg0eOaZZ/A3S3OTeDClpaUYMGAAysrKUF5ejtGjR+OdGr6QhE6nQ1RUFEJCQvC///1PbXNU\nIzQ0FAEBAfD29oavry8yMzPNpnVLgdDpdAgPD8fevXsRHByM6OhobNq0CRE1dPjmgQMHULduXUyd\nOrVGC0R+fj7y8/PRrVs3FBUVoUePHti2bVuN/V0UFxfDz88PlZWViI2NxbJlyxAbG6u2WaqxfPly\nHD9+HPfu3cOOHTvUNkc1WrdujePHj6OhcJ4bM7jlVBuZmZkICwtDaGgofH19MWnSJGzfvl1ts1Sj\nX79+aMAvP1eDadasGbr9NT943bp1ERERgauW5sj2cPz+mlekvLwcOp1OlkPwVK5cuYLdu3dj5syZ\n1LEF8jv3uKVA5OXloYVgIpuQkBDk8ZP3EASA3NxcZGVlISYmRm1TVKOqqgrdunXDgw8+iIEDB6JD\nhw5qm6Qaf//737F06VJ4OXsJQDdAo9FgyJAhiIqKwmeffWYxrVs+LY2zFvwlPIKioiKMHz8eH330\nEerWrau2Oarh5eWFX375BVeuXMGPP/6IjIwMtU1ShZ07d6Jp06aIjIyk6AHAwYMHkZWVhT179uDf\n//43DggXOjHCLQVCzjgKomZSUVGBcePG4fHHH8eYMWPUNsclqF+/Ph5++GEcO3ZMbVNU4dChQ9ix\nYwdat26Nxx57DPv27cNUJUsJehhBf03X3KRJEzzyyCMWG6ndUiDkjKMgah6MMcyYMQMdOnTAXOE8\n2DWQwsJC3L59GwBQUlKC7777DpGRkSpbpQ7/+te/oNVqcfHiRWzevBmDBg3Sj7GqaRQXF+PeX3Pd\n379/H+np6ehsYe1ktxQI4TiKDh06YOLEiTW2pwoAPPbYY+jTpw/Onj2LFi1a1NgxIwcPHsSGDRuw\nf/9+REZGIjIyEmn80m81jGvXrmHQoEHo1q0bYmJiMGrUKAwePFhts1yCmlxFff36dfTr10//uxg5\nciSGCRemMcItu7kSBEEQzsctIwiCIAjC+ZBAEARBEJKQQBAEQRCSkEAQBEEQkpBAEG6Ht7e3vpdS\nZGQkLl++rLZJDiElJQVNmjTBM888Y1c+ixYtwvvvv6/fP3z4sNk8S0tL0a1bN9SqVQs3b960q1zC\n81Blum+CsAc/Pz9kZWVJnuM75bljV0aNRoPHHnsMK1asMDlXWVkJHx95/67G975nzx4kJCRIpq1d\nuzZ++eUXtG7dWrnBhMdDEQTh9uTm5iI8PBzTpk1D586dodVqsXTpUvTs2RNdu3bFokWL9Gnffvtt\nhIeHo1+/fpg8ebL+TTsuLg7Hjx8HwA0y4x2mTqfDiy++qM/r008/BQBkZGQgLi4Ojz76KCIiIvD4\n44/ryzh69Cj69u2Lbt26oVevXigqKsKAAQNw8uRJfZrY2FjJmXeFvc5TUlKQmJiIwYMHY+jQobh/\n/z6GDBmCHj16oEuXLqIZSYX3debMGVGe+/btw5AhQ/D7778jJiYGkZGR6Nq1K86dO2frIydqCBRB\nEG5HSUmJflRwmzZtsHz5cpw7dw7r169Hz549kZ6ejnPnziEzMxNVVVUYPXo0Dhw4AD8/P6SmpuLk\nyZOoqKhA9+7dERUVBYB765aKOlavXo3AwEBkZmairKwMsbGx+oFFv/zyC7KzsxEUFIS+ffvi0KFD\niIqKwqRJk/Dll1+iR48eKCoqQp06dTBjxgykpKTggw8+wNmzZ1FWVmZxBCtPVlYWfv31VwQGBkKn\n0+Gbb75BvXr1UFhYiN69eyMxMRHHjx83e1+FhYXw9fVFvXr18Mknn+D555/H5MmTUVlZicrKSkd9\nJYSHQgJBuB116tQRVTHl5uaiVatW6NmzJwAgPT0d6enpehG5f/8+cnJycO/ePYwdOxa1a9dG7dq1\nZU3Pkp6ejl9//RVbtmwBANy9exfnzp2Dr68vevbsiebNmwMAunXrhosXL6JevXoICgpCjx49AEA/\nWeD48ePx5ptvYunSpVizZg2efPJJq2VrNBoMGzYMgYGBALjZWRcsWIADBw7Ay8sLV69exfXr13Hg\nwAGT++IjkfT0dMTHxwMA+vTpg7fffhtXrlzB2LFjERYWZv1hEzUaqmIiPAJ/f3/R/oIFC5CVlYWs\nrCycPXsWTz31FABxFY5w28fHB1VVVQC4hlshK1eu1Od1/vx5DBkyBIwx1KpVS5/G29sblZWVZts+\n/Pz8MHToUGzbtg1fffUVpkyZIuu++DUdAGDjxo0oLCzEiRMnkJWVhaZNm6K0tBQajcbkvng70tLS\nMHz4cADclCz/+9//UKdOHYwYMQL79++XZQNRcyGBIDyO+Ph4rFmzBvfv3wfArR9y48YN9O/fH9u2\nbUNpaSnu3buHnTt36q8JDQ3Vz3bKRwt8Xv/5z3/01TFnz55FcXGxZLkajQbh4eG4du2aPq979+5B\np9MBAGbOnIm//e1v6NmzJ+rXr2/1Poxnwbl79y6aNm0Kb29v7N+/H5cuXYJGozF7X4wxnDp1Cl27\ndgUAXLx4Ea1bt8acOXMwevToGr36ICEPqmIi3A6pt3ThsaFDh+L06dPo3bs3AKBevXrYsGEDIiMj\nMXHiRHTt2hVNmzZFdHS03gnPnz8fEyZMwKeffoqHH35Yn9/MmTORm5uL7t27gzGGpk2b4ptvvjHb\nZs4TFPIAAAEHSURBVOHr64vU1FTMmTMHJSUl8PPzw3fffQd/f390794d9evXl1W9xN+TsIwpU6Zg\n1KhR6NKlC6KiovQTVBrfF1/Vdvz4cdEMrl9++SXWr18PX19fBAUFYeHChbLsIGouNFkfUWNZvHgx\n6tatixdeeKFayrt69SoGDhxo0suI57///S+OHTuGjz/+2CHlvf3222jXrh0mTJhgNa2SdYqJmgNV\nMRE1muoaL7Fu3Tr06tUL//rXv8ymqVOnDvbs2WP3QDmehQsXWhUHfqBcZWUlLcdJmEARBEEQBCEJ\nvTIQBEEQkpBAEARBEJKQQBAEQRCSkEAQBEEQkpBAEARBEJKQQBAEQRCS/D/5ezxaVcA+sAAAAABJ\nRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Calculate moments  \n",
      "-------------------"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mom, text = S.moment(nr=4)\n",
      "print('sigma = %g, m0 = %g' % (sa, sqrt(mom[0])))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "sigma = 0.472955, m0 = 0.472955\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Section 2.2.1 Random functions in Spectral Domain - Gaussian processes\n",
      "--------------------------------------------------------------------------\n",
      "Smoothing of spectral estimate \n",
      "----------------------------------\n",
      "By decreasing Lmax the spectrum estimate becomes smoother."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "Lmax0 = 200; Lmax1 = 50\n",
      "S1 = ts.tospecdata(L=Lmax0)\n",
      "S2 = ts.tospecdata(L=Lmax1)\n",
      "S1.plot('-.')\n",
      "S2.plot()\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAZEAAAEXCAYAAABsyHmSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      " Estimated autocovariance\n",
      "----------------------------\n",
      "Obviously knowing the spectrum one can compute the covariance\n",
      "function. The following code will compute the covariance for the \n",
      "unimodal spectral density S1 and compare it with estimated \n",
      "covariance of the signal xx."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "Lmax = 85\n",
      "R1 = S1.tocovdata(nr=1)   \n",
      "Rest = ts.tocovdata(lag=Lmax)\n",
      "R1.plot('.')\n",
      "Rest.plot()\n",
      "axis([0, 25, -0.1, 0.25])\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEXCAYAAACDChKsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUAIhhBAiE0oghBBCZEIJhBBCiEz+H72XH4/yYkS0AAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can see in Figure below that the covariance function corresponding to the spectral density S2 significantly differs from the one estimated directly from data. It can be seen in Figure above that the covariance corresponding to S1 agrees much better with the estimated covariance function."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "R2 = S2.tocovdata(nr=1)\n",
      "R2.plot('.')\n",
      "Rest.plot()\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEXCAYAAACDChKsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npTCBEBGRUphAiIhIKUwgRESklP8PMsK4ELXZVjoAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Section 2.2.2 Transformed Gaussian models\n",
      "-------------------------------------------\n",
      "We begin with computing skewness and kurtosis for the data set xx and compare it with the second order wave approximation proposed by Winterstein:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import wafo.stats as ws\n",
      "rho3 = ws.skew(xx[:, 1])\n",
      "rho4 = ws.kurtosis(xx[:, 1])\n",
      "\n",
      "sk, ku = S1.stats_nl(moments='sk')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Comparisons of 3 transformations"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "import wafo.transform.models as wtm\n",
      "gh = wtm.TrHermite(mean=me, sigma=sa, skew=sk, kurt=ku).trdata()\n",
      "g = wtm.TrLinear(mean=me, sigma=sa).trdata() # Linear transformation \n",
      "glc, gemp = lc.trdata(mean=me, sigma=sa)\n",
      "\n",
      "glc.plot('b-') #! Transf. estimated from level-crossings\n",
      "gh.plot('b-.') #! Hermite Transf. estimated from moments\n",
      "g.plot('r')\n",
      "grid('on')\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAETCAYAAADecgZGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSfEXQggrJMVfCCGs0P8A797ScbJhOE8AAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Test Gaussianity of a stochastic process\n",
      "------------------------------------------\n",
      "TESTGAUSSIAN simulates  e(g(u)-u) = int (g(u)-u)^2 du  for Gaussian processes given the spectral density, S. The result is plotted if test0 is given. This is useful for testing if the process X(t) is Gaussian.\n",
      "If 95% of TEST1 is less than TEST0 then X(t) is not Gaussian at a 5% level.\n",
      "\n",
      "As we see from the figure below: none of the simulated values of test1 is above 1.00. Thus the data significantly departs from a Gaussian distribution. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "test0 = glc.dist2gauss()\n",
      "# the following test takes time\n",
      "N = len(xx)\n",
      "test1 = S1.testgaussian(ns=N, cases=50, test0=test0)\n",
      "is_gaussian = sum(test1 > test0) > 5 \n",
      "print(is_gaussian)\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "False\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEKCAYAAAASByJ7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nY0it2QAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Normalplot of data xx\n",
      "------------------------\n",
      "indicates that the underlying distribution has a \"heavy\" upper tail and a \"light\" lower tail."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "import pylab\n",
      "ws.probplot(ts.data.ravel(), dist='norm', plot=pylab)\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEWCAYAAACNJFuYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAIWDiIgE/ABEguqfnObDqQAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Section 2.2.3 Spectral densities of sea data\n",
      "-----------------------------------------------\n",
      "Example 2: Different forms of spectra"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import wafo.spectrum.models as wsm\n",
      "clf()\n",
      "Hm0 = 7; Tp = 11;\n",
      "spec = wsm.Jonswap(Hm0=Hm0, Tp=Tp).tospecdata()\n",
      "spec.plot()\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYkAAAEXCAYAAABYsbiOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Directional spectrum and Encountered directional spectrum\n",
      "=========================================================\n",
      "Directional spectrum\n",
      "---------------------"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "D = wsm.Spreading('cos2s')\n",
      "Sd = D.tospecdata2d(spec)\n",
      "Sd.plot()\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEXCAYAAACtTzM+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Encountered directional spectrum\n",
      "--------------------------------- "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#clf()\n",
      "#Se = spec2spec(Sd,'encdir',0,10);\n",
      "#plotspec(Se), hold on\n",
      "#plotspec(Sd,1,'--'), hold off\n",
      "##!wafostamp('','(ER)')\n",
      "#disp('Block = 17'),pause(pstate)\n",
      "#\n",
      "##!#! Frequency spectra\n",
      "#clf\n",
      "#Sd1 =spec2spec(Sd,'freq');\n",
      "#Sd2 = spec2spec(Se,'enc');\n",
      "#plotspec(spec), hold on\n",
      "#plotspec(Sd1,1,'.'),\n",
      "#plotspec(Sd2),\n",
      "##!wafostamp('','(ER)')\n",
      "#hold off\n",
      "#disp('Block = 18'),pause(pstate)\n",
      "#\n",
      "##!#! Wave number spectrum\n",
      "#clf\n",
      "#Sk = spec2spec(spec,'k1d')\n",
      "#Skd = spec2spec(Sd,'k1d')\n",
      "#plotspec(Sk), hold on\n",
      "#plotspec(Skd,1,'--'), hold off\n",
      "##!wafostamp('','(ER)')\n",
      "#disp('Block = 19'),pause(pstate)\n",
      "#\n",
      "##!#! Effect of waterdepth on spectrum\n",
      "#clf\n",
      "#plotspec(spec,1,'--'), hold on\n",
      "#S20 = spec;\n",
      "#S20.S = S20.S.*phi1(S20.w,20);\n",
      "#S20.h = 20;\n",
      "#plotspec(S20),  hold off\n",
      "##!wafostamp('','(ER)')\n",
      "#disp('Block = 20'),pause(pstate)\n",
      "#\n",
      "##!#! Section 2.3 Simulation of transformed Gaussian process\n",
      "##!#! Example 3: Simulation of random sea    \n",
      "##! The reconstruct function replaces the spurious points of seasurface by\n",
      "##! simulated data on the basis of the remaining data and a transformed Gaussian\n",
      "##! process. As noted previously one must be careful using the criteria \n",
      "##! for finding spurious points when reconstructing a dataset, because\n",
      "##! these criteria might remove the highest and steepest waves as we can see\n",
      "##! in this plot where the spurious points is indicated with a '+' sign:\n",
      "##!\n",
      "#clf\n",
      "#[y, grec] = reconstruct(xx,inds);\n",
      "#waveplot(y,'-',xx(inds,:),'+',1,1)\n",
      "#axis([0 inf -inf inf])\n",
      "##!wafostamp('','(ER)')\n",
      "#disp('Block = 21'),pause(pstate)\n",
      "#\n",
      "##! Compare transformation (grec) from reconstructed (y) \n",
      "##! with original (glc) from (xx)\n",
      "#clf\n",
      "#trplot(g), hold on\n",
      "#plot(gemp(:,1),gemp(:,2))\n",
      "#plot(glc(:,1),glc(:,2),'-.')\n",
      "#plot(grec(:,1),grec(:,2)), hold off \n",
      "#disp('Block = 22'),pause(pstate)\n",
      "#\n",
      "##!#!\n",
      "#clf\n",
      "#L = 200;\n",
      "#x = dat2gaus(y,grec);\n",
      "#Sx = dat2spec(x,L);\n",
      "#disp('Block = 23'),pause(pstate)\n",
      "#      \n",
      "##!#!\n",
      "#clf\n",
      "#dt = spec2dt(Sx)\n",
      "#Ny = fix(2*60/dt) #! = 2 minutes\n",
      "#Sx.tr = grec;\n",
      "#ysim = spec2sdat(Sx,Ny);\n",
      "#waveplot(ysim,'-')\n",
      "##!wafostamp('','(CR)')\n",
      "#disp('Block = 24'),pause(pstate)\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Estimated spectrum compared to Torsethaugen spectrum\n",
      "-------------------------------------------------------"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "clf()\n",
      "fp = 1.1;dw = 0.01\n",
      "H0 = S1.characteristic('Hm0')[0]\n",
      "St = wsm.Torsethaugen(Hm0=H0,Tp=2*pi/fp).tospecdata(np.arange(0,5+dw/2,dw))  \n",
      "S1.plot()\n",
      "St.plot('-.')\n",
      "axis([0, 6, 0, 0.4])\n",
      "show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAEXCAYAAAC6baP3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ncQghhLCIJA4hhBAW+X/+nuw44UNfwAAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Transformed Gaussian model compared to Gaussian model\n",
      "-------------------------------------------------------\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dt = St.sampling_period()\n",
      "va, sk, ku = St.stats_nl(moments='vsk' )\n",
      "#sa = sqrt(va)\n",
      "gh = wtm.TrHermite(mean=me, sigma=sa, skew=sk, kurt=ku, ysigma=sa)\n",
      " \n",
      "ysim_t = St.sim(ns=240, dt=0.5)\n",
      "xsim_t = ysim_t.copy()\n",
      "xsim_t[:,1] = gh.gauss2dat(ysim_t[:,1])\n",
      "\n",
      "ts_y = wo.mat2timeseries(ysim_t)\n",
      "ts_x = wo.mat2timeseries(xsim_t)\n",
      "ts_y.plot_wave(sym1='r.', ts=ts_x, sym2='b', sigma=sa, nsub=5, nfig=1)\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD9CAYAAAC1DKAUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n"
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}